In today’s dynamic and competitive business environment, maintaining reliability, operational availability, energy efficiency, and productivity of assets is paramount for organisations operating in the oil and gas (O&G) sector. Remote monitoring and management systems have emerged as indispensable tools in achieving these objectives by providing real-time data on asset performance.
Role of key systems in driving O&G sector
APM and AIM systems
Nowadays, organisations strive to maintain the reliability, operational availability, energy efficiency and productivity of their assets. To this end, asset performance management (APM) and asset integrity management (AIM) systems play a crucial role by providing real-time data on asset performance. Organisations can prevent downtime and increase operational availability by monitoring assets and addressing potential issues proactively. Additionally, these systems contribute towards energy efficiency by identifying areas to reduce energy consumption, reducing operational costs and promoting sustainability. In this continuous changing market scenario, these systems enable organisations to adapt quickly, optimise asset performance and make data-driven decisions.
As an integral part of risk management, AIM focuses on minimising safety risks, improving asset reliability, and reducing regulatory compliance and business risk through comprehensive data-driven assessment to enable informed equipment strategies and maintenance decisions. Besides, the primary focus of this risk-based approach is to improve efficiency, increase uptime and reduce both capital and operating expenditure. A robust AIM solution helps operators optimise existing assets’ service lives and their overall operational performance.
Strategy formulation and management systems
Strategy formulation and management systems help drive asset management practices by enabling thorough asset integrity and criticality analysis. Through comprehensive assessments and condition monitoring, organisations develop well-informed strategy development plans that outline actions to maintain asset integrity and optimise life cycle management. Categorising assets based on asset criticality requires prioritised maintenance efforts and resource allocation. Integration of various asset management processes through enterprise resource planning (ERP) systems is required to enhance decision-making. Strategies integrated with action plans establish proactive preventive measures for compliance, including inspection, maintenance and safety protocols, thus reducing incidents and downtime while optimising asset performance. Many organisations have committed to sustainable asset management practices by using these systems.
Asset health monitoring
Asset health monitoring is another system that is crucial for optimising performance and maintaining the health of assets in the O&G sector. Continuous assessment of processes and lubrication conditions allows for early detection of abnormalities and deviations from optimal parameters. Vibration analysis through online and offline data collection helps identify faults and establish historical trends for accurate diagnostics. Temperature monitoring, both online and offline, detects abnormal operating conditions and potential equipment failures. Monitoring factors such as current, speed, meaningful operating data and corrosion provide insights into asset performance and integrity. Further, analysis of equipment performance data and health history enables formulation of proactive maintenance strategies. Integration of real-time and discrete parameters allows for data-driven decisions and optimised maintenance schedules.
Operation-driven asset reliability
Operation-driven asset reliability is a critical aspect of the O&G sector, which ensures optimal performance and minimises disruptions. Key elements of this approach are instant awareness, reflection and action on deviations at site. By leveraging advanced monitoring and data analytics technologies, organisations can swiftly detect and analyse deviations from expected asset performance. Instant awareness enables real-time insight into asset conditions, allowing operators to promptly identify potential issues and take immediate corrective action. Furthermore, operation-driven asset reliability systems provide recommendations on how to address deviations effectively. These recommendations consider historical data, best practices and industry standards, empowering operators with actionable insights. To ensure continuous improvement, recommendation tracking is implemented to monitor the effectiveness of the proposed actions and fine-tune strategies for future asset reliability enhancements. This allows organisations to continually improve their asset management strategies and ensure the safe and efficient operation of critical assets.
Predictive analysis with different models
Predictive analysis in the O&G sector has undergone significant advancement with the integration of machine learning (ML), deep learning (DL), artificial intelligence (AI) and thermodynamic models. These technologies offer powerful tools to detect deviations and mitigate emergency situations through sensoring.
By analysing historical and real-time data, ML algorithms can identify patterns and anomalies that may indicate potential equipment failures or safety risks. DL techniques further enhance this analysis by processing large volumes of data and extracting complex patterns that may be difficult to detect by traditional analytical methods. Additionally, AI algorithms recommend appropriate actions to mitigate risks based on past incidents. When combined with thermodynamic mapping, which involves subject matter expert intervention, predictive analysis leads to better utilisation of alerts and assets. The thermodynamic mapping curve, created through the collaboration of domain experts and AI systems, helps in comparing real-time data with expected performance. This approach enables early identification of deviations, allowing operators to take proactive measures to prevent failures or suboptimal performance.
The integration of machines and systems with internet of things (IoT) hubs unlocks previously unavailable insights, empowering asset supervisors to devise effective solutions, prevent disruptions, and solve long-standing problems. Smart asset monitoring and management transform assets into valuable resources that generate additional revenue. The remarkable technological progress over the past two decades has revolutionised data storage and processing, replacing conventional methods with advanced analytical applications suitable for big data. Thus, it has reduced costs and enhanced decision-making across multiple sectors, transforming problem-solving models in the industry.
Key challenges in achieving asset integrity and reliability
One of the key challenges in achieving asset integrity and reliability in the O&G sector is problem definition. Without a clear understanding of the problem, it can be difficult to identify the root cause and implement effective solutions. Therefore, it is important for organisations to align their teams and ensure that everyone is working towards the same goal.
Another challenge is the need for continuous monitoring and data analysis. Assets in the O&G sector are subject to a wide range of conditions, and it is important for organisations to continuously monitor key parameters to identify any deviations from expected performance. This will help organisations quickly identify any potential issues and be prepared to take corrective action before they become critical.
In order to overcome these challenges and achieve asset integrity and reliability in the O&G sector, it is important for organisations to develop a comprehensive strategy that includes problem definition, continuous monitoring and data analysis, and regulatory compliance. Further, there is a need to have a comprehensive approach to address the root causes as well as improve operational performance and cost savings.
The way forward
The future of APM and AIM in the O&G sector holds tremendous potential for driving operational excellence, safety and sustainability. The integration of advanced technologies such as data analytics, IoT, digital twins, robotics and automation will revolutionise the way assets are monitored, maintained and optimised. By harnessing the power of real-time data, predictive analytics and remote monitoring capabilities, organisations can proactively identify asset issues, optimise maintenance schedules and improve reliability. Moreover, the increasing focus on sustainability and environmental impact will drive the adoption of APM and AIM solutions that prioritise energy optimisation, emission reduction and responsible asset management.
As the O&G sector continues to evolve and face new challenges, APM and AIM systems will play a pivotal role in ensuring the long-term success and competitiveness of organisations. By embracing these technologies and approaches, companies can navigate the complexities of the industry, enhance stakeholder confidence and drive sustainable growth in the future. w
Based on remarks by Pradeep K., Senior Manager, Central Maintenance and Reliability Organisation, Bharat Petroleum Corporation Limited, at a recent Indian Infrastructure conference
